Long-Term Evolution (LTE) is the next step in cellular Third-Generation (3G) systems, which represents basically an evolution of present mobile communications standards, such as Universal Mobile Telecommunication System (UMTS) and Global System for Mobile Communications (GSM) [1]. It is a Third Generation Partnership Project (3GPP) standard that provides throughputs up to 50 Mbps in uplink and up to 100 Mbps in downlink. It uses scalable bandwidth from 1.4 to 20 MHz in order to suit the needs of network operators that have different bandwidth allocations. LTE is also expected to improve spectral efficiency in networks, allowing carriers to provide more data and voice services over a given bandwidth.
LTE-Advanced (LTE-A), an evolution of LTE, is being standardized in LTE Release 10 and beyond. It is aimed at fulfilling International Mobile Telecommunications (IMT)-Advanced requirements, whose capabilities go beyond those of IMT-2000 and include enhanced peak data rates to support advanced services and applications (100 Mbps for high mobility, and 1 Gbps for low mobility).
So far, LTE-Advanced foresees the use of up to eight transmit antennas at the base stations. In order to address huge increases in the average cell spectral efficiency, massive Multiple-Input Multiple-Output (MIMO) systems are currently being investigated as future extensions of LTE-Advanced for Release 12 and beyond [2]. These systems typically comprise several hundreds of low-power antennas, where the degrees of freedom in excess at transmission allow for a variety of signal processing possibilities in transmission and reception. These large MIMO systems are currently subject to intense research. Other wireless standards, such as IEEE 802.11, consider also the use of multiple antenna techniques for either spatially multiplexing several data streams or tailoring the radiated beams towards a given direction in space.
Some solutions are aimed at increasing spatial focusing of energy into specific directions, therefore addressing users more sharply [3]. So-called Time Reversal Beamforming (TRBF) focuses electromagnetic energy by means of probing the channel and time-reversing the received signals prior to transmission as described in patent U.S. Pat. No. 8,330,642-B2 “Imaging by Time Reversal Beamforming. Other more traditional beamforming solutions involve tailoring the radiated pattern, so that beams oriented towards different users present minimum overlapping in order to minimize inter-user interference.
In parallel with these research topics, inter-cell interference remains as a fundamental limitation in wireless systems. In massive MIMO systems, where the received signal to noise (SNR) values can be significantly enhanced with the massive use of beamforming, interference from neighbour cells can also be enhanced in the same factor by the beamforming process thus resulting in significant signal degradation. Furthermore, interference will likely present intermittent patterns according to the scheduler operation at the base stations, while employing modulation and coding schemes (MCS) which are in principle unknown to the victim user. Both drawbacks complicate the operation of Successive Interference Cancellation (SIC) receivers as stated by A. Ruegg et al. [6].
3GPP standards foresee several mechanisms for inter-cell coordination in order to manage interference. So-called enhanced Inter-Cell Interference Coordination (eICIC) deal with several solutions for inter-cell coordination, namely Almost Blank Subframes (ABS)-based eICIC and Carrier Aggregation (CA)-based eICIC [4]. Both solutions rely on coordinated resource sharing between the victim and the aggressor cell(s) in the time and frequency domains, respectively. ABS-based eICIC allows coordination of time resources in the form of a pattern of protected subframes, by which the aggressor cell relinquishes access to its users in order to alleviate the interference created towards the victim cell. CA-based eICIC coordinates frequency resources through use of Carrier Aggregation so that different spectrum is used for potentially interfered users. These solutions can be especially useful in heterogeneous network deployments.
However, in the context of massive MIMO systems the aforementioned solutions are not efficient as they are mainly intended for non-massive MIMO systems, where users are scheduled in time and frequency dimensions and no advantage is taken from the spatial dimension. Traditional sharing of time and frequency resources involves the whole set of beams in massive MIMO systems, while interference from an aggressor cell is usually caused by only one beam or a limited set of beams. More efficient inter-cell coordination schemes should aim at alleviating interference at user (or beam) level instead of cell level, thereby coordinating only the concrete resources which are in conflict between victim and aggressor cells, be it in time, frequency or space dimensions.
More specific solutions for inter-cell coordination are therefore needed for alleviating interference in massive MIMO deployments due to the use of advanced beamforming.